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dc.contributor.authorYeomans, CM
dc.contributor.authorClaridge, H
dc.contributor.authorHudson, AJL
dc.contributor.authorShail, RK
dc.contributor.authorWillems, C
dc.contributor.authorEyre, M
dc.contributor.authorHarker, C
dc.date.accessioned2022-12-01T10:06:23Z
dc.date.issued2022-11-28
dc.date.updated2022-11-30T16:51:24Z
dc.description.abstractSemi-automated algorithms incorporating multi-sourced datasets into a single analysis are increasingly common, but until now operate at a fixed pixel resolution resulting in multi-sourced methods being limited by the largest input pixel size. Multi-scale lineament detection circumvents this issue and allows increased levels of detail to be captured. We present a semi-automated method using a bottom-up Object-Based Image Analysis approach to map regional lineaments to a high level of detail. The method is applied to onshore LiDAR data and offshore bathymetry around the Land's End Granite (Cornwall, UK). The method uses three different pixel resolutions to extract detailed lineaments across a 700 km2 area. The granite displays large-scale NW-SE fault zones that are considered analogous to those being targeted as onshore deep geothermal reservoirs (2-5 km in depth). Investigation of the lineaments derived from this study show along-strike variations from NW-SE orientations within granite to NNW-SSE within slate and reflect structural inheritance of early Variscan structures within Devonian slates. This is furthered by analysing these major structures for reservoir potential. Lineaments proximal to these broadly NW-SE features indicate a damage zone approximately 100-200 m wide is present. These observations provide a preliminary understanding of reservoir characteristics for fault-hosted geothermal systems.en_GB
dc.description.sponsorshipNatural Environment Research Council (NERC)en_GB
dc.identifier.citationPublished online 28 November 2022en_GB
dc.identifier.doihttps://doi.org/10.1144/qjegh2022-051
dc.identifier.grantnumberNE/S003886/1en_GB
dc.identifier.grantnumberNE/L002434/1en_GB
dc.identifier.grantnumberNE/S004769/1en_GB
dc.identifier.urihttp://hdl.handle.net/10871/131916
dc.identifierORCID: 0000-0001-7200-5124 (Shail, Robin K)
dc.identifierORCID: 0000-0002-5506-674X (Eyre, Matthew)
dc.language.isoenen_GB
dc.publisherThe Geological Societyen_GB
dc.rights© 2022 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License (http://creativecommons.org/licenses/by/4.0/). Published by The Geological Society of London.en_GB
dc.titleA single multi-scale and multi-sourced semi-automated lineament detection technique for detailed structural mapping with applications to geothermal energy explorationen_GB
dc.typeArticleen_GB
dc.date.available2022-12-01T10:06:23Z
dc.identifier.issn1470-9236
dc.descriptionThis is the author accepted manuscript. The final version is available on open access from the Geological Society via the DOI in this recorden_GB
dc.descriptionData availability: The bathymetry data used in this study have been sourced from the UK Hydrographic Office and accessed via the Admiralty Marine Data Portal. The LiDAR data used in this study have been sourced from the Centre for Ecology and Hydrology. The British Geological Survey is thanked for making the BGS Geology 625k (DiGMapGB- 625), BGS Geology 250k (DiGMap250k) and BGS Geology 50k (DiGMapGB-50) data available on an Open Government Licence.en_GB
dc.identifier.eissn2041-4803
dc.identifier.journalQuarterly Journal of Engineering Geology and Hydrogeologyen_GB
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2022-11-17
rioxxterms.versionAMen_GB
rioxxterms.licenseref.startdate2022-11-28
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2022-12-01T10:03:19Z
refterms.versionFCDAM
refterms.dateFOA2022-12-01T10:06:25Z
refterms.panelBen_GB
refterms.dateFirstOnline2022-11-28


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© 2022 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License (http://creativecommons.org/licenses/by/4.0/). Published by The Geological Society of London.
Except where otherwise noted, this item's licence is described as © 2022 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License (http://creativecommons.org/licenses/by/4.0/). Published by The Geological Society of London.